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Gene expression profiling during all-trans retinoic acid-induced cell differentiation of acute promyelocytic leukemia cells

  • Lijun Yang(corresponding author)
    ,
  • Hongshan Zhao
    ,
  • Shi Wu Li
    ,
  • Kim Ahrens
    ,
  • Christine Collins
    ,
  • Sarah Eckenrode
*Corresponding author for this work
Scholary Output:
Contribution to journal
Article
Peer-review

Open access

Abstract

Using cDNA microarrays we determined the gene expression patterns in the human acute promyelocytic leukemia (APL) cell line NB4 during all-trans retinoic acid (ATRA)-induced differentiation. We analyzed the expression of 12,288 genes in the NB4 cells after 12 hours, 24 hours, 48 hours, 72 hours, and 96 hours of ATRA exposure. During this time course, we found 168 up-regulated and more than 179 down-regulated genes, most of which have not been reported before. Many of the altered genes encode products that participate in signaling pathways, cell differentiation, programmed cell death, transcription regulation, and production of cytokines and chemokines. Of interest, the CD52 and protein kinase A regulatory subunit α (PKA-R1α) genes, whose products are being used as therapeutic targets for certain human neoplasias in currently ongoing clinical trials, were among the genes observed to be markedly up-regulated after ATRA treatment. The present study provides valuable data to further understand the mechanism of ATRA-induced APL cell differentiation and suggests potential therapeutic alternatives for this leukemia.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 212-221 (10 pages)

Journal (Volume, Issue Number)

Journal of Molecular Diagnostics (Volume 5, Issue 4)

Publication milestones

  • Published - 11/2003

Publication status

Published - 11/2003

ISSN

1525-1578

Publication IDs

  • Scopus: 0242691738
  • PubMed: 14573779
  • ORCID: /0000-0002-3040-3631/work/227033602

Publication metrics

Metrics

SciVal
FWCI
0.61
SciVal
Author count
9
SciVal
citations
27
SciVal
Paper percentile
75
Scopus
citations
Fractional count
2
Fractional count
0.22
Fractional count
7
Fractional count
0.78
Fractional count
2
Fractional count
1

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Citation count
37
Captures
31